Deep RL is a rapidly developing area of research, finding application in areas as diverse as game playing, robotics, natural language processing, computer vision, and systems control [1]}. Deep RL involves an agent that interacts with an environment with the aim of developing a policy that maximises long term return of rewards. Deep RL has a framework that allows for generic problem solving that is not dependent on pre-existing domain knowledge, making these techniques applicable to a wide range of problems.
